ORI GIN AL PA PER

Exploring uncertainties in a marketplace for cloudcomputing: a revelatory case study

Sabrina Hauff • Jan Huntgeburth • Daniel Veit

� Springer-Verlag Berlin Heidelberg 2014

Abstract Today, highly standardized information technology (IT) resources such

as storage and processing power are becoming available and affordable to all.

Therefore, IT managers evermore focus on reducing the costs and risks that these

resources entail rather than on the benefits or competitive edge they provide. A

marketplace for cloud computing represents a promising alternative for obtaining

standardized IT resources in a highly flexible and scalable manner. Based on a

revelatory case study of a cloud market project, we show that uncertainties are

prevalent in cloud markets and that the principal-agent theory is an adequate per-

spective to study and explain these uncertainties. By triangulating data from formal

and informal interviews, documentations and project meetings, we develop a second-

level contextual understanding of uncertainties in the relationships between market

operator, cloud providers and users. Our analysis reveals that while cloud market

operators have capabilities to mitigate uncertainties between cloud provider and user,

they also cause new uncertainties from the cloud provider and user perspective. As an

outcome, we present a framework that sheds light on the uncertainty trade-offs

involved in the decision to adopt a cloud market by cloud providers and users.

Keywords Cloud computing � e-Markets � Adoption � Case study �Uncertainty � Principal-agent theory

JEL Classification M15

S. Hauff (&) � J. Huntgeburth � D. Veit

School of Business and Economics, University of Augsburg,

Universitatsstr. 16, 86135 Augsburg, Germany

e-mail: sabrina.hauff@wiwi.uni-augsburg.de

J. Huntgeburth

e-mail: jan.huntgeburth@wiwi.uni-augsburg.de

D. Veit

e-mail: veit@wiwi.uni-augsburg.de

123

J Bus Econ

DOI 10.1007/s11573-014-0719-3

1 Introduction and motivation

Cloud computing causes fundamental changes within the IT industry and IT service

delivery. Hence, it has received much attention in research and practice over the last

years. Current trends show that the market for cloud computing has an immense

potential: Gartner expects that the public cloud services market grows from 2012 to

2016 worldwide from $109 billion to $206.6 billion (Gartner 2012). The German

Federal Association for Information Technology, Telecommunications and New

Media (BITKOM) predicts a double-digit growth rate from 2012 to 2016 within the

German cloud computing market, growing from 5.3 billion euro to 17.1 billion euro

in 2016 (BITKOM 2012). Nonetheless, many researchers think that cloud computing

is still in its infancy because challenges like data privacy, security management,

virtual machine migration, or a market-oriented resource management have not yet

received sufficient attention (Armbrust et al. 2010; Buyya et al. 2009b; Zhang et al.

2010).

A research topic that emerged only recently deals with the idea of an electronic

marketplace (e-market) for cloud computing. Buyya et al. (2008) first introduced the

concept of a cloud exchange that allows participants to locate cloud providers and

users with an appropriate offer. Cloud providers can use marketplaces as additional

sales channels to increase the utilization of their existing infrastructure. Cloud users

can benefit from an improved price transparency and reduced search costs for

suitable trading partners since a marketplace can preselect suitable providers based

on a user’s preferences and list them all clearly, to name but a few examples.

However, though there is considerable research on e-market adoption examining the

phenomena in various contexts—most of it focuses on studying e-markets in

scenarios where tangible goods are traded (e.g., Chang and Wong 2010;

Gengatharen and Standing 2005; Joo and Kim 2004; Quaddus and Hofmeyer

2007; Tao et al. 2007).

We believe that the motives for adopting a transparent, two sided and

independently managed marketplace for cloud computing are partly distinct from

those identified in previous research on e-markets. First of all, traditional

economic market theories are not applicable in this context. Especially in

economics, markets have been researched for a long time. They can provide an

optimal allocation mechanism for supply and demand. This idea can be dated back

to Smith (1937) who developed the idea of an ‘‘invisible hand’’ guiding an

efficient resource allocation. Yet, theories about efficient markets only hold under

certain simplifying conditions: full information transparency has to be given and

all information has to be included in the market price, so that no uncertainties are

prevalent (Malkiel and Fama 1970). Beyond these simplifying assumptions,

markets are especially well working for highly standardized goods (Williamson

1985) and it has to be assumed that security and data privacy challenges are

absent. Yet, these conditions are not given in a real-world cloud computing

context, as various information asymmetries and uncertainties that arise from those

asymmetries exist. We think that they can be largely attributed to the interesting

characteristics of a cloud computing product which differentiate it from many

traditional goods traded on marketplaces: As nowadays highly standardized IT

S. Hauff et al.

123

resources have become available and affordable to all, IT managers evermore

focus on the risks and costs that these IT resources entail rather than on the

benefits or competitive edge these computing resources can provide (Carr 2003).

In cloud computing, vendor lock-in and non-availability of a service pose such

risks and thus cause large obstacles in cloud computing adoption, for example.

Besides that, when enterprises use a cloud product, they have to transfer their

business data to the cloud which is under control of the provider. As remotely

hosted data can never be fully protected against unauthorized access, additional

uncertainties like privacy and security concerns can explain the reluctance of some

organizations to engage in cloud computing (Armbrust et al. 2010). In

consequence, the level of involvement and risk regarding cloud computing

products is much higher than for tangible products or highly standardized services

(e.g. electricity or package tours) traded on other marketplaces, where no massive

amounts of data are transferred to third-party hosted infrastructures.

Thus, we propose that the success of a marketplace for cloud computing highly

depends on the robustness of the marketplace’s properties to manage uncertainties

influencing the business relationship between providers and users. This implies

especially that the way the marketplace operator designs, implements and operates

the marketplace is critical for its success. Therefore, we focus on the research

question: How do uncertainties influence the decision to adopt either a transparent,

two sided and independently managed marketplace or a direct provisioning mode

for cloud computing?

Overall, this paper is expected to make the following contributions to the

literature on cloud computing. To our best knowledge, our study presents the first

framework for understanding the uncertainty trade-offs involved in the decision to

adopt a public, two sided and independently managed marketplace for large-scale,

commoditized computing resources such as clouds. This framework extends

previous research on e-markets by examining in-depth the uncertainties surrounding

cloud markets and the way they influence the marketplace adoption decision from a

cloud provider and user perspective. Thus, we provide a comprehensive picture

which takes into account not only all participants, namely providers, users, as well

as the marketplace operator, but also the various relationships between them and the

uncertainties arising out of them. Drawing on principal-agent theory, we show that

agency problems are prevalent in cloud markets and that their management is

critical for the feasibility of a cloud market. From a practical perspective, our

framework can be utilized to inform the design of a marketplace for cloud

computing, e.g. using experience operating a public market from other domains.

The remaining parts of the paper are structured as follows. The next section

positions the paper in the field by introducing the key concepts and the literature-

based pre-understanding of the phenomenon. Section three presents the context of

the study and gives a methodological overview of our revelatory case study. In

section four, our results and interpretations are presented. Finally, the last section

discusses the key findings, theoretical contributions, areas for future research and

practical implications.

Exploring uncertainties in a marketplace for cloud computing

123

2 Theoretical foundation

2.1 Cloud computing: service and deployment model

Cloud computing is a global, distributed, service-centric model for delivering IT-

based solutions which offers to users a new elasticity of resources without paying a

premium for large scale (Bakos 1991). Cloud services provide computing resources

in different levels of abstraction. Infrastructure-as-a-Service (IaaS) provides

hardware resources like processing and storage. Platform-as-a-Service (PaaS)

offers, in addition to the infrastructure, a cloud software development environment

to build, test, and deploy cloud applications (Foster et al. 2008). Lastly, Software-

as-a-Service (SaaS) provides complete applications running on cloud infrastructure

which is completely managed and controlled by the provider. Next to these three

well established service types, the term Everything-as-a-Service (XaaS) is often

used as generalization to show that not only infrastructure, platform, and software is

offered as a service but also Business, Data, or Human, for example (Lenk et al.

2009). The idea of a cloud market—as examined in our study—is to trade highly-

standardized computing resources such as processing capacity and storage.

Therefore, we only focus on IaaS in the following.

Three types of deployment models can be differentiated, namely private, public,

and hybrid clouds which differ in organizational aspects like ownership and the

degree of control while they rely on the same technology (Zhang et al. 2010).

Private clouds are typically owned and managed by a single company. While they

offer the highest degree of control over performance, security, and reliability,

private clouds do not offer the typical advantages of clouds like no up-front capital

costs (Grance and Mell 2011). In contrast, public clouds are typically owned, built

and managed by a third party and available to the general public. While there is no

fundamental difference in the underlying technical concepts compared to private

clouds, the consumer’s control over data, network, and security is limited (Armbrust

et al. 2010). Moreover, hybrid clouds are a composition of the deployment models

described above. The distinct cloud infrastructures remain unique entities, but are

linked to enable data and application portability (Grance and Mell 2011). As the

idea of a marketplace for cloud computing is to match third party cloud providers’

excess capacity and users’ demand of computing resources, within our study we

focus on public clouds.

Armbrust et al. (2010) argue that three aspects are new in public cloud computing

from a user perspective. First, public clouds offer the illusion to users of having

access to an infinite amount of resources when needed. Second, computing

resources can be elastically provisioned and released outward and inward

commensurate with demand in a pay-as-you-go manner. Third, up-front investments

are eliminated allowing companies to start small and increase resources only when

there is an increase in their demand. These aspects promise a faster time to market

(Grance and Mell 2011), lower upfront IT costs (Venters and Whitley 2012) and an

easier scale out (Alford and Morton 2009). Compared to conventional data centers,

public clouds benefit from higher economies of scale due to very large data centers.

Moreover, they exploit higher utilization by multiplexing of workloads from

S. Hauff et al.

123

different organizations, simplify operation and increase utilization via resource

virtualization (Armbrust et al. 2010).

2.2 Marketplaces for cloud computing

A marketplace is a space where goods and services are traded. An e-market is an

inter-organizational information system that is designed to establish provider-user

relationships (Bakos 1998). It facilitates communication and transactions between

its participants, often supported by additional services (Stockdale and Standing

2004). The activities normally are trilateral including users, providers, and the firm

operating the marketplace, often referred to as the intermediary or marketplace

operator (Chang and Wong 2010).

Literature discusses different functions and characteristics of markets (Bakos

1998; Coase 1937; Wigand 1997). Bakos (1998) distinguishes three main functions

of markets; namely matching buyers and sellers, facilitating transactions and

providing an institutional infrastructure. In the setting of cloud economics, these

market functions have to be adapted to the concrete nature of cloud computing. In

concrete, cloud markets aim to match users’ demand of IT resources with supply,

i.e. providers’ excess capacity (Li and Jeng 2010). Second, cloud markets stem from

the facilitation of transactions between the user and provider of IT resources (Buyya

et al. 2008). To fulfill the transaction, the service has to be provisioned to the user

while the payment must be transferred to the provider. Cloud markets typically

incorporate mechanisms for these logistic and settlement activities. To protect users

and providers from the opportunistic behavior of other market participants, cloud

markets normally ensure a certain level of trust, e.g. through including banks issuing

letters of credit, credit reporting bureaus, or rating agencies. Finally the institutional

infrastructure of cloud markets, which provides a legal and regulatory framework to

govern market transactions, is of high importance for the market’s success

(Rossbach and Welz 2011). In particular, this relates to issues about contract law,

dispute resolution, and data privacy protection, but also offers mechanisms for their

enforcement. Seen in light of Wigand (1997), we characterize the cloud market as

competitive, due the variety of buyers and sellers, the homogenous nature of

computing resources, easy entrance to and departure from the market, low switching

costs for consumers and close to perfect information.

Table 1 gives an overview of the literature that deals with marketplaces for cloud

computing. This literature has been gathered by conducting a literature review in the

top eight IS journals based on the Association for Information Systems (AIS) Senior

Scholars’ Basket of Journals (AIS 2011) using the search strings ‘‘market’’ or

‘‘trading platform’’ in combination with ‘‘cloud computing’’ in a full text search. We

then manually checked all papers for their relevance. Since this yielded almost no

results, we conducted a broader literature review using the search engines

EBSCOhost, ScienceDirect, ProQuest, and Google Scholar. Thereby, we used the

search terms ‘‘market’’ or ‘‘trading platform’’, again both in combination with

‘‘cloud computing’’, and, in the case of Google Scholar, also the terms

‘‘marketplace’’ and ‘‘cloud computing’’ as well as ‘‘market exchange’’ and ‘‘cloud

computing’’ to further limit the results. Moreover, we conducted a backward and

Exploring uncertainties in a marketplace for cloud computing

123

forward search with all identified papers. As can be seen, the topic has not received

much attention so far. The focus of the research is on generally motivating the topic,

on architecture and on technological aspects like standardized application

programming interfaces (APIs), software components that handle the reservation

and allocation of resources, and other implementation issues. However, to our best

knowledge no study exist which empirically examines the adoption of a marketplace

for cloud computing. We aim to fill this research gap through our study, focusing on

the role of uncertainties that are prevalent between the different parties of a

marketplace scenario.

There is considerable research on e-market adoption (e.g., Chang and Wong

2010; Quaddus and Hofmeyer 2007; Rask and Kragh 2004). As e-marketplaces

evolved from EDI systems (Angeles 2000) and are supported by information and

communication technologies (Malone et al. 1987), researchers have drawn possible

determinants of e–market adoption from these areas.

We believe that the motives for adopting a marketplace for cloud computing are

partly distinct to those identified in previous research on e-markets. On the one

hand, uncertainties play a major role for a decision-maker whether to adopt cloud

computing or not and thus explain the reluctance of some organizations to engage in

cloud computing (Armbrust et al. 2010). On the other hand, IT is nowadays the

backbone of commerce and its core functions—storage, processing and network—

have become available and affordable to all. As argued by Carr (2003), if resources

are essential to competition but inconsequential to strategy, the uncertainties they

create become more important to companies than the advantages they provide. The

diminishing role of IT has important implications for understanding the adoption of

a marketplace for cloud computing. We propose that the market success of a cloud

market will highly depend on the ability of the market operator to manage and

mitigate uncertainties between cloud providers and users compared to bilateral

cloud service scenarios. Today, disruptive IT innovation can paralyze a company’s

ability to produce its products, deliver its services and connect with its customers

(Carr 2003). Hence, IT managers—at least for infrastructure technology—often

focus on vulnerabilities, rather than opportunities for gaining competitive advan-

tage. In many cases, this creates an atmosphere of fear-driven IT-management rather

Table 1 Literature regarding marketplaces for cloud computing

References Topics

Buyya et al. (2008) Motivation, architecture

Buyya et al. (2009a) Architecture, technologies

Buyya et al. (2009b) Motivation, architecture

Krieger et al. (2010) Motivation, challenges, architecture, technologies, API, prototype

Li and Jeng (2010) Architecture, negotiation mechanisms

Garg et al. (2011) Requirements, architecture, prototype

Breskovic et al. (2012) Standardization, SLAs

Calheiros et al. (2012) Architecture, prototype

Grilo and Jardim-Goncalves (2013) Architecture

S. Hauff et al.

123

than a challenge oriented leadership. However, little is known about cloud-specific

uncertainties derogating the provider-user relationship and cloud-market-specific

uncertainties introduced and mitigated by the marketplace operator. Therefore, we

will focus on these aspects in the following.

2.3 Uncertainties surrounding cloud marketplaces

We draw on the principal-agent theory to develop a legitimate frame and potentially

useful vocabulary to enter the field (cf. Fig. 1). We have chosen principal-agent

theory because it particularly allows us to address the relations between the cloud

provider, user and market operator. It focuses on the existing information

asymmetries in these relations and the arising uncertainties and involved trade-

offs when parties evaluate whether or not to enter into a contract. Other theories are

not so suitable in shedding light on these issues. For example, Eisenhardt (1989a)

contrasts several organizational theories with agency theory, like the contingency

theory or the transaction cost theory. While they share some underlying

assumptions, several others are not met by all these contrasted theory. We will

not discuss all of them in detail here (see Eisenhardt (1989a) for more information).

However, especially the transaction cost theory has similar assumptions like

information asymmetries, goal conflicts, bounded rationality, or self-interests of all

parties. Yet, it differs in the aspect of risk preference by assuming risk neutrality as

opposed to an often assumed risk aversion of the agent. Moreover, it offers an

explanation as to which governance structure (market vs. hierarchy or hybrid form)

is chosen based on the occurring transaction costs to reach an agreement between

parties that exchange goods. Transaction costs can be divided into production costs

and costs associated with operation risks and opportunism risks. In addition, the

transaction cost theory deals with demand uncertainty and market volatility as

sources of uncertainty or economic theories that represent a future benefit as a form

of uncertainty (Williamson 1985). Before we contrast principal-agent theory and

transaction cost theory, we first introduce the former one in detail.

Fig. 1 Pre-understanding of uncertainties surrounding cloud markets

Exploring uncertainties in a marketplace for cloud computing

123

Agency problems befall almost all kinds of economic transactions where bounded

rationality, fears of opportunism and information asymmetry exist (e.g., employment:

Schepers et al. 2012; relationships of psychiatrists with industry: Appelbaum & Gold

2010; financial policy: Mugge 2011). An agency problem occurs when one party (the

principal) delegates work to another party (the agent) and the welfare of the principal is

affected by the choices of the agent. Principal-agent theory applies to any variation of

relationships where one party is offering a service and the other party is providing

compensation for the service. Agency problems can arise from two sources, adverse

selection and moral hazard. Adverse selection arises due to a pre-contractual

misrepresentation of providers’ true abilities and qualities as well as the presentation of

false service quality information (Akerlof 1970). In the context of cloud computing,

providers can be seen as agents and users take the role of principals. Thus, while providers

have hidden information about their true qualities, cloud users cannot easily determine a

suitable cloud provider out of a pool of high-quality and low-quality providers. Thereby,

the quality of a provider can for example relate to the effort he puts into fulfilling agreed

upon service level agreements (SLAs) as well as the quality of his data centers. A moral

hazard occurs due to a post-contractual shirking of the provider by not accomplishing a

task as promised (Jensen and Meckling 1976). Even more, it also includes provider’s

deliberate deception of users since they cannot easily evaluate providers’ performance.

Principal-agent theory suggests three measures to overcome the agency problem.

Agents can design and send signals to the principal to expose private information about

their true qualities (e.g. in-depth information about how they operate their service)

(Bakos 1997). The principal examines these signals and may change concerns on using

the agent’s service (Rao and Ruekert 1994). Incentives are designed to prevent

opportunistic behavior of the agent by making any hidden actions irrational or costly

(Pavlou et al. 2007). They can help to align the interests of cloud users and providers

more closely. For example, the user can offer monetary incentives to the provider based

on the quality of the outcome (Vermillion et al. 2002). Finally, principals can also

reduce uncertainties by monitoring the agents’ activities, e.g. by auditing and

controlling the principal randomly (Strausz 1997). In a nutshell, while signaling

provides one solution to adverse selection problems, incentives as well as monitoring

can especially help to resolve moral hazard problems (Mishra et al. 1998).

Overall, the principal-agent theory can help us to analyze the relationship

between cloud users, cloud providers and the market operator as follows: First of all,

it can guide us to understand the potential uncertainties which may exist in the cloud

provider-user relationship by revealing the motives and interest of users and

providers and by interpreting the information asymmetries between the two parties.

Especially the quality of cloud services can hardly be evaluated by the user at any

point in time since the technological details and the behavior of the marketplace

operator and the cloud provider are hidden from him. Therefore, these services are

best described as credence goods. Cloud users’ on-going assessment whether or not

to continue using a cloud service whose quality is hard to discern puts special

emphasis on the importance of uncertainty in our scenario. Large information

asymmetries characterize the prevalent situation in today’s cloud computing

landscape: While the cloud provider has perfect information about his services, the

user does not know about many aspects like future availability of a service, the way

S. Hauff et al.

123

his data is used by the cloud provider, etc. Even more, the user has no chance in

gaining access to this information, even if he has a high willingness to pay for it

(e.g. for monitoring services). The described situation relates well to the concepts of

hidden information and hidden action of the principal-agent theory and is thus

considered as a well-suited theoretical perspective to guide our data collection and

analysis. Principal-agent theory has been successfully used as a theoretical lens to

study uncertainties with regards to search goods (Pavlou et al. 2007) and experience

goods (Dimoka et al. 2012) traded on online markets. In contrast to cloud services,

the quality of the search and experience goods can be either evaluated before the

purchase decision or upon consumption (Nelson 1970). Therefore, we believe that

principal-agent theory is an appropriate lens to study bilateral information

asymmetries between different actors on the cloud market. Moreover, the

perspective allows us to analyze how the introduction of a marketplace influences

this relationship. Yet, a marketplace does not only reduce uncertainties between

cloud users and providers, it also establishes two new agency problems: one

between the user (principal) and the marketplace operator (agent) and another one

between the provider (principal) and the marketplace operator (agent). As in these

relationships goal conflict, fears of opportunism and asymmetric information are

again prevalent, the principal-agent theory can be also utilized to interpret the

uncertainties introduced by the marketplace operator and to understand how these

uncertainties can be successfully reduced.

The transaction cost theory can be clearly demarcated from this: In this theory,

uncertainties are described as arising from market volatility and demand

uncertainty. Even more, the focus of the two theories is different: While the output

of the transaction cost theory is a decision about which governance structure should

be favored (hierarchy vs. market or hybrid forms), the principal-agent theory offers

insights into the relationship of a principal and an agent and investigates what

tactical situations might occur between them by considering potential conflicts,

trade-offs, incentives and control mechanisms. We are especially interested in the

latter point and thus see the principal-agent theory as very valuable for guiding our

research. Yet, our intention is not to test the principal-agent theory in the context of

cloud markets or find instantiations of the concepts in our data. Rather, the

principal-agent theory can be seen as a ‘‘snapshot of our theoretical sensitivity’’

(Sarker et al. 2012, p. 320) to guide data collection and interpretation.

3 The context of study and methodological overview

3.1 Context: case background

We examine the acceptance of a marketplace for cloud computing in the unique

context of a financial marketplace operator specialized in trading shares and other

securities (MarketMaker) who is located in the EU. MarketMaker has decided to

launch a marketplace for IaaS-resources after a 1-year evaluation phase. In this

evaluation phase, a prototype was set up and cloud providers and users were

involved to examine the feasibility of such a marketplace. We name the prototype

Exploring uncertainties in a marketplace for cloud computing

123

CloudMarket in the following. During this phase, we were able to accompany the

marketplace operator and conduct this case study by in-depth experience at any

stage of the evolution of the project.

CloudMarket is a trading platform for highly standardized computing resources.

MarketMaker provides this platform and thereby has the role of a neutral third-party

marketplace operator. It acts only as an intermediary between cloud providers and

users and therefore does not sell own cloud resources. The marketplace mainly

arouses interest among medium and large sized companies since it allows high

volume trading of cloud resources. In the following, we explain the functionality of

CloudMarket in detail and outline the services MarketMaker offers as intermediary.

To become a player on the marketplace, cloud providers and users have to

fulfill certain admission criteria. Cloud providers have to prove that they offer

high-quality services with respect to data security, privacy and reliability based

on certificates issued by third party auditing. Cloud users have to prove that they

have sufficient liable equity to pay for cloud services. In addition, both cloud

providers and users have to agree to the terms and conditions as well as the code

of conduct established by MarketMaker. Once they have been accepted as

marketplace participants, the cloud providers can enter bids while the cloud users

can enter requests for resources. CloudMarket offers two types of markets: a spot

market, where cloud services are sold and delivery takes place immediately, and

a derivatives market, where a gap between trading and delivery is present. The

spot market allows for a flexible, short-term allocation of resources with a

referenced price while the derivatives market enables securing prices through the

hedging of future demand. Thus, it also offers an indicator of future prices. In

each of these markets, computing power and storage resources can be traded. The

definition of standards for IaaS resources as well as contracts is one key

requirement for the marketplace. It enables transparency and allows for a

comparison of services on the one hand and reduces the effort for negotiations on

the other hand. As currently no standards exist, MarketMaker wants to set

standards for each cloud service class. While technical parameters like I/O-

performance and security requirements are fixed, the participants can choose

between predefined values for tradable units, SLAs, the allocation model, and the

product location. The SLAs are kept very simple and define the quality of service

to be expected, metrics for user support, and a refund policy in case SLAs are

violated. The allocation model can have two types: open and fixed end. Open end

means that the contract period is unlimited, has a certain cancellation period for

the contract partners, and includes a scalable function. It allows users an increase

of their contracted resources up to a predefined size under the same conditions. In

a fixed end allocation model, the contract duration is fixed, no cancellation period

exists, and no scalable function is included. Concerning the product location, the

CloudMarket differentiates between data centers located in the European Union

and data centers located within US territory. All these variable parameters can be

combined. To give an example of one occurrence: A product from the asset class

‘‘storage’’ might have a tradable unit of one terabyte, is located in the EU, the

allocation model is open end, and the SLA used is ‘‘SLA1’’ which is the highest

quality available on the marketplace.

S. Hauff et al.

123

CloudMarket supports four phases: pre-trading, trading, clearing, and settle-

ment. We explain the phases and the services MarketMaker offers in each of

these phases. Aim of the pre-trading phase is to allow for an adjustment of the

product portfolio as well as specific parameters, e.g. the adjustment of product

benchmarks or bandwidth due to technological progress. In the trading phase, a

provider or a user can select such a product and enter the quantity he wants to

trade on the marketplace as well as the price he is willing to pay or sell the

resources for. A two-sided auction mechanism is used to determine the matching

of bids and asks. Once the trading has been done, the trade has to be cleared. In

the spot market, the participants clear bilaterally, e.g. via a clearing bank, while

in the derivatives market, a central counterparty (CCP) handles the clearing.

A CCP is an entity which steps in between user and provider. Thereby, it acts as

provider for each user and as user for each provider. Introducing a CCP has

efficiency related reasons because every participant has only one party to interact

with. Next, the settlement takes place. In this step, the user and the provider who

have entered into a contract are connected dynamically and securely by a self-

developed software. Once the connection is established, the consumer can utilize

the resources. At the same time, the settlement software is also monitoring the

provider to check whether he is fulfilling the contract. In case he is violating the

agreement, the refund policy as defined in the SLAs takes effect. This is an

improvement from the current situation where users have to monitor the service

themselves and make claims against the providers.

While the CloudMarket project team has clear ideas about the overall design and

has developed a prototype with a technology partner, a fully implemented and

launched solution of the marketplace does not yet exist.

3.2 Methodology

We believe that the CloudMarket project is a revelatory, unique and exemplary

source of insight on our topic (Yin 2009). MarketMaker is a successful

marketplace operator in the financial sector with a strong reputation. As

trustworthiness of the marketplace operator may be seen as a necessary condition

to establish a cloud market, the CloudMarket project is seen by both providers and

users as a serious alternative to obtain and dispose computing resources. Thus, the

ecology of the CloudMarket project team and its potential business partners

represents a fascinating context where the topic of interest could be investigated in

depth. The goal of our study is to generalize our empirical insights to a theory on

the phenomenon under investigation based on analytical generalization (Yin

2009).

Our engagement with the CloudMarket project contributed to our broader

understanding of the cloud market business case. The first author was

accompanying the project scientifically for half a year. She was present at team

meetings and had access to all internal documents. In addition to reviewing

internal documents, many informal conversations with the team members helped

her to establish a fundamental knowledge of how the marketplace will work and

to understand the opportunities and risks involved in this project. Even more, she

Exploring uncertainties in a marketplace for cloud computing

123

was allowed to participate in some of the meetings with potential consumers and

providers which provided her with additional valuable insights from the

participants’ perspectives.

Moreover, the first author conducted twelve formal interviews with project team

members, cloud providers and users. Overall, twelve interviews were conducted

between April and July 2012: six interviews on the cloud user side, four interviews

on the cloud provider side, and two interviews with representatives of the

marketplace operator. The companies interviewed belong to different branches and

the interviewees held different positions. Aim of this spread of interview partners

was to gain as many insights as possible and triangulate data from different sources

as suggested by methodologist (Patton 2002).

Table 2 provides an overview of the interviews conducted, describing the

industry of the company interviewed, the position of the interviewee in his

company, whether the interview was carried out face to face or via telephone, and

information about the length of the interview.

Each interview was recorded and conducted based on an interview guide (Yin

2009). The interview guide kept interactions focused while allowing individual

experiences to emerge and thus, best used the limited time available in the interview

situation (Gordon 1980). Interview partners were asked questions about their

understanding of cloud computing, their current usage or provision of cloud

resources as well as the opportunities and risks of using cloud computing from their

perspective. Moreover, the marketplace prototype was introduced and the oppor-

tunities and challenges it offers were discussed in depth. The interview guide served

as a ‘‘reminder regarding the information that needs to be collected’’ (Yin 2009,

p. 86). After each interview, the interview guide was adapted in case new

uncertainty concepts have emerged.

Overall, our approach can be characterized as interpretive in that sense that it

takes the interview partners’ experiences with cloud computing to develop a

‘‘second-order theoretical understanding’’ of uncertainties surrounding cloud

markets (Lee 1991; Sarker et al. 2012). In doing so, we applied a less procedural

version of the grounded theory methodology as proposed by Sarker and Sarker

(2009) to develop our understanding of uncertainties surrounding cloud markets.

This involved constant comparison of the data ‘‘[…] to see if [they] support and

continue to support the emerging categories’’ (Holton 2007, p. 277) and then to link

this evolving set of concepts to higher level categories of uncertainties (Walsham

1995). This process led to the discovery of cloud- and market-specific uncertainties

surrounding the market. Finally, based on the experiences of our interview partners,

we identified capabilities of the market place that could help to reduce the

uncertainties surrounding cloud markets (Walsham 1995). Once, concepts and

patterns emerged we enfolded previous literature to support our interpretations

which involved to ask ‘‘what is this similar to, what does it contradict, and why’’

(Eisenhardt 1989b, p. 544).

S. Hauff et al.

123

4 Interpretation and results

In the following, we present our results and interpretations of uncertainties prevalent

in cloud markets and ways to successfully mitigate these uncertainties. We start

with cloud-specific uncertainties which exist between the cloud provider and user.

Next, we discuss capabilities of the market operator to reduce these uncertainties.

As the way the marketplace platform has been designed, implemented and is now

operated by the market maker not only reduces but also introduces new

uncertainties, we analyze cloud-market specific uncertainties between the market

Table 2 Interview partners

Role in

the

market

Industry Position of interviewee(s) Way of

communication

Length of

interview

(min)

User Information technology Interview partner 1

Enterprise Account Manager

& Partner Relations

Face to face 40

User Bank Interview partner 2

Manager of the Architecture

Department

Interview partner 3

Enterprise Architect

Face to face 60

User Logistics Interview partner 4

Management position in

R&D

Telephone 60

User Automobile Interview partner 5

Leader Vitas & Cloud

Computing,

Interview partner 6

Assistant of Cloud Team

Telephone 40

Provider Internet service provider Interview partner 7

Chief Operating Officer

Telephone 50

Provider Internet service provider Interview partner 8

Product Manager

Telephone 45

Provider Internet service provider Interview partner 9

Management position in

R&D

Telephone 40

Provider IT-consultancy, IT-services Interview partner 10

Business Developer

Telephone 55

Market

operator

Equity-, equity index-,

interest rate derivatives,

clearing services

Interview partner 11

Project leader of the

CloudMarket team

Interview partner 12

Consultant—responsible for

the functional work stream

of the project

Face to face 45

Exploring uncertainties in a marketplace for cloud computing

123

operator and its participants up next. Finally, we discuss how a cloud market

operator can successfully mitigate these cloud-market specific uncertainties. The

outcome is a framework which can be used by cloud market operators, cloud

providers and users to understand and successfully manage uncertainties surround-

ing cloud markets.

4.1 Cloud-specific uncertainties

Cloud-specific uncertainties arise through user’s disbelief about the cloud provider’s

ability (adverse selection) or willingness (moral hazard) to provide the computing

resources as agreed upon (Pavlou et al. 2007). Interviewees expressed several types

of concerns that may hinder the adoption of cloud computing. An overview of the

identified uncertainties is depicted in Fig. 2. The concerns presented in the

following are not specific to cloud markets but may occur in all kinds of cloud

computing service scenarios.

First of all, interviewees argued that users have information privacy concerns in

adopting cloud computing. According to Westin (1967, p. 7), privacy refers to ‘‘the

claim of individuals, groups or institutions to determine for themselves when, how

and to what extent information about themselves is communicated to others’’. In the

context of cloud computing, users want several types of data to be protected by the

cloud provider. These include identity information, transaction histories, and,

probably most important, all business critical data which might be transferred to the

provider for processing or storage (Takabi et al. 2010).

‘‘[…] we have repeatedly tested cloud usage in certain business areas.

However, we have repeatedly shied away because we realized that some

internal bank data would be stored in the cloud. We did not want to take this

risk.’’ (interview partner 3)

Privacy concerns arise in both types of agency problems: Ex ante, users may find

it difficult to analyze a cloud provider’s mechanisms to ensure data privacy. Ex post,

a user cannot easily check whether the cloud provider is disclosing his data to third

parties or whether he is using it otherwise without the user’s consent, for example.

Fig. 2 Uncertainties between cloud provider and user

S. Hauff et al.

123

These concerns have been confirmed by several interview partners on the cloud

provider side.

‘‘One aspect of virtualizing storage is that we need the trust of users. They

have to be confident that we handle their data according to their data privacy

requirements without telling them where the data is actually stored.’’

(interview partner 6)

The important role of information privacy is also supported by previous research

on e–commerce. E.g., Pavlou et al. (2007) show that purchasing behavior in online

exchange environments is influenced by information privacy concerns. Thus, we

may generalize their findings to the context of cloud computing.

Apart from information privacy concerns, interviewees also mentioned informa-

tion security concerns. Information security relates to the secure transmission and

storage of information and the prevention of information theft (Miyazaki and

Fernandez 2000). The topic is closely related to information privacy and the

uncertainties which arise are similar. Again, adverse selection and moral hazard

problems can be identified: Pre-contractually, it is difficult to examine the installed

security mechanisms of the provider and thus to judge the provider’s ability of

safeguarding all information. Post-contractually, the user cannot observe whether

the cloud provider is successfully protecting the data from hackers and espionage

attempts, for instance. This is a major concern of most users.

‘‘[…] the amount of data passed to [the provider] needs to be highly

technically secured.’’ (interview partner 4)

Also previous cloud computing opinion papers stressed the importance of data

security for cloud computing. E.g. Kaufman (2009, p. 62) emphasizes the necessity

of establishing security measures in the cloud as they ‘‘[…] offer the opportunity for

simultaneous attacks to numerous sites, and without proper security, hundreds of

sites could be comprised through a single malicious activity […]’’. These concerns

have been confirmed by several interview partners on the user and cloud provider

side.

Furthermore, availability concerns constitute another fear of users. Availability

refers to the ‘‘reliable and predictable delivery of services from the cloud’’ (Sandhu

et al. 2010). In this case, especially adverse selection problems are prevalent: The

consumer cannot evaluate a provider’s effort and investments in the reliability of his

infrastructure, e.g. whether he really mirrors all data to a second data center. Having

entered into a relationship, he can measure the actual uptime of the service.

However, he still cannot predict the future availability and thus faces uncertainty

‘‘We have in general much higher availability requirements as those offered

by typical cloud providers. […] But here is the problem: the requirements, or

that what is delivered from a cloud provider is certainly not enough. […]

However, availability and confidentiality are important criteria for choosing

our [IT] products.’’ (interview partner 3)

Exploring uncertainties in a marketplace for cloud computing

123

While availability concerns have not been connected to user’s uncertainty in

previous research, our findings indicate that, in the context of cloud computing,

availability is a major source of uncertainty (Sandhu et al. 2010).

The fourth user concern which emerged in our interviews is provider lock-in.

Since cloud products are currently not standardized, e.g. proprietary APIs are

prevalent, users may not as easily extract their data and change from one provider to

another (Armbrust et al. 2010). In this case, uncertainty arises due to adverse

selection problems: users know that choosing one cloud provider will result in a

lock-into a particular technology. Since a migration to another provider is very

costly, consumers are dependent on the provider and therefore vulnerable to price

increases and availability problems, for instance. Moreover, the triability of a

service is not given which increases the pressure on the consumer to select an

appropriate provider. These aspects are supported by several interview partners but

have also been discussed in the literature (Armbrust et al. 2010).

‘‘And then there is another important problem: how is my vendor lock-in, i.e.

how can I extract my data that belongs to me out of the data center again.’’

(interview partner 7)

To sum it up, key requirements for storage and processing power are services that

are compliant, secure, reliable and interoperable. Whether these requirements are

sufficiently met is highly dependent on the decisions of the cloud provider. As goal

conflict, fears of opportunism and asymmetric information are prevalent between

cloud provider and user, these types of uncertainties will influence the users’

decision whether to adopt and use cloud computing.

4.2 Mitigating capability of a cloud marketplace operator

E-commerce and electronic markets came with the claim of disintermediation: the

elimination of mediating roles such as wholesalers, retailers, or brokers, which

allows for a direct linkage of buyers and sellers (Wigand 1997). Currently, the cloud

landscape is organized mostly without intermediaries. Yet, as discussed in the

previous section and as outlined by Datta and Chatterjee (2008), an e-market still

faces uncertainties, even in the light of reduced search and communication costs.

This can lead to a reintermediation, the introduction of an online intermediary.

Research shows that an intermediary is seen as a source of trust and integrity of an

e-market (e.g., Giaglis et al. 2002; Son et al. 2006).

Thus, in our case, the introduction of a marketplace with a third-party

independent operator can serve as an uncertainty mitigator between users and

cloud providers. An overview of the mitigating capabilities of a cloud marketplace

is depicted in Fig. 3. Signaling can be one effective method of overcoming

uncertainties. Through the way the marketplace is implemented, it supports cloud

providers in signaling: When providers participate in the marketplace, they

automatically show that they have a certain quality because the marketplace

operator has defined admission criteria they have to fulfill; otherwise they are not

allowed to participate. Moreover, providers can just easily list all of their product

S. Hauff et al.

123

characteristics at the marketplace to show that they do not fear the comparison but

offer a sufficiently high level of quality.

‘‘I do think that this has advantages. So if a company is in such a business

case, I would say, not only information about prices, but also information

about the providers, would be a big advantage for this company. So as an

example: […] How are its computer centers distributed around the world?

Who is the provider? Where does the provider operate? What are his

priorities?’’ (interview partner 5)

Providers could still try to deceive consumers by not delivering the promised

quality. Nonetheless, at least the perceived uncertainty is reduced by increased

transparency. These two signaling methods help to reduce uncertainties. In addition,

the marketplace anticipates some of the risks and uncertainties by supporting further

signaling activities, e.g. providing warranties to consumers if services are not

available and thereby reducing the availability concerns.

‘‘So, it’s about the guarantee granted by the marketplace operator. […] There

can’t be something like, ‘No, we cannot deliver right now. You receive money,

or something like a coupon as compensation.’ […] It must be delivered in any

case; the guarantee must be given. And I think if that’s the case, then you have

again a very important added value that you sell here, namely warranty.’’

(interview partner 1)

Even more, marketing research shows that there is a strong relationship between

brands and trust. Delgado-Ballester and Munuera-Aleman (2001) confirmed that, on

the one hand, high satisfaction with a brand creates trust and, on the other hand, trust

leads to a higher commitment to and involvement with a brand. Thus, the brand

name of the marketplace operator is a good signal. MarketMaker has a good

reputation and is known as a trustworthy partner. Therefore, it does not want to risk

this image by providing a marketplace where low quality products are traded. This

is confirmed not only by the marketplace operator, it is also the perception the

Fig. 3 Uncertainty reduction through marketplace operator

Exploring uncertainties in a marketplace for cloud computing

123

interviewees from the provider and user side had. Thus, it successfully decreases

existing concerns.

‘‘So I think if the right brand operates the marketplace, simply more trust is

created. As customer, I would assume that if a provider is admitted to the

marketplace, […] the provider has been tested and meets a certain level of

quality.’’ (interview partner 10)

Monitoring and incentivizing are further methods of mitigating user concerns. On

the one hand, the marketplace operator can implement a functionality which

monitors the actual availability of a cloud service that has been traded over the

marketplace. If the availability requirements are permanently not fulfilled, they have

to face consequences like suspension. Moreover, the marketplace operator can also

monitor privacy or security breaches, at least if they become publicly known, and

exclude the involved providers. In addition, the marketplace operator could

establish feedback functionalities where users can share their experiences with

certain providers. Although this functionality is currently not planned to be

implemented on the CloudMarket, it has been mentioned in interviews as potential

uncertainty mitigation mechanism.

‘‘I think, seen from a user perspective, it would be great if I could get in touch

with other users of this cloud provider. […] You can contact another

reference, […] without the providers’ active control, which of course makes

the entire thing transparent again.’’ (interview partner 10)

While incentivizing can help to reduce all types of concerns discussed above,

monitoring can especially help to reduce information privacy and information

security concerns as well as availability concerns.

Furthermore, MarketMaker intends a standardization of IaaS-resources and a

migration functionality to easily switch from one provider to another. If this

standardization is widely accepted and the migration functionality is working, it

would have a huge impact on the user-provider relationship since it can eliminate all

lock-in concerns.

‘‘So, I believe that standardization can only be good for the market. I believe

that the entire cloud industry is currently struggling with the fact that the

forecasts are huge but volume does not turn out as planned. I think the

reluctance of the German market is right on this issue.’’ (interview partner 10)

4.3 Cloud-market-specific uncertainties

The marketplace operator also introduces new uncertainties. First, the relationship

between the marketplace operator and the consumer is analyzed: While the user still

has the same goals as before when trading resources over the marketplace, namely

buying resources based on criteria like price, privacy, security, and availability, the

marketplace operator is new in this whole picture. He is offering several services to

the user, the most important one being the matching of the consumers’ requirements

and the providers’ offerings. The marketplace operator aims at earning money with

S. Hauff et al.

123

these services with as little effort as possible. Thus, his goals are profit-oriented and

not congruent with the user’s goals. Moreover, the activities of the marketplace

operator are difficult to assess by the user, e.g. how the operator is selecting suitable

trading partners and how the monitoring of the providers’ cloud services is working.

Therefore, the chance for opportunistic behavior is given: The marketplace operator

could select providers for the matching based on where he can make the largest

profits and not based on suitability, for instance.

The uncertainties in the user-marketplace-operator relationship take many forms

and comprise adverse selection as well as moral hazard problems. Concerns about

the neutrality of the marketplace operator were issued by the interviewees.

Neutrality refers to ‘‘not taking sides, impartiality and indifference in the scientific

sense of an impartial disinterest with respect to the outcome of any conflict’’ (Hoffer

1985). In this case, the interviewees were especially concerned about the neutrality

in the selection process of the provider which cannot be assessed upfront.

‘‘I also think is important that it is a very reputable and solid marketplace

operator, one who is neutral. A marketplace operator, of which I do not expect

to make the most profit out of its services, but simply compares the companies

in a neutral way.’’ (interview partner 6)

Moreover, the interview partners mentioned concerns about the technological

ability of the marketplace operator and his ability to set standards. The marketplace

operator also confirmed the existence of these concerns. They exist especially pre-

contractually: Users cannot easily evaluate the technological ability to build the

marketplace and therefore its quality. In addition, at least shortly after the

marketplace goes live, consumers are uncertain whether the standard of the

marketplace will prevail. While the marketplace operator can reduce the availability

concerns inherent in the user-provider relationship, the users named additional

availability concerns regarding the marketplace.

‘‘One disadvantage is: what happens if I rely mostly or solely on the

marketplace? […] It is possible that the marketplace is not available and in

case a company is used to lease resources on a short-term base, then it could

run into a bottleneck.’’ (interview partner 4)

These concerns exist ex ante and ex post since the user can never determine the

future uptime of the marketplace and the operator’s efforts to ensure a high

availability rate.

Lastly, the soundness of all functionalities of the marketplace and the activities of

its operator are also seen critical because their evaluation is neither pre-

contractually nor post-contractually possible in an easy way. This also includes

concerns about information security and privacy.

‘‘[…] it must be possible to assure that the service provided by the

marketplace operator is working in terms of reliability, risk management,

market supervision and all the other topics.’’ (interview partner 12)

Concerning the cloud provider-marketplace operator relationship, the provider

still has the same goals as before: He wants to maximize his profit with minimal

Exploring uncertainties in a marketplace for cloud computing

123

efforts, while the marketplace operator wants to maximize his profits as well.

However, these goals are not congruent, since the provider wants to sell as many of

his cloud resources as possible while the marketplace wants to conduct as many

matchings as possible, yet, not necessarily with the same provider. The provider

cannot easily observe the behavior and the activities of the marketplace operator,

e.g. how the marketplace operator is selecting suitable trading partners and whether

he can really evaluate the quality of a provider and his services. Thus, the chance for

opportunistic behavior is again given.

The uncertainties which arise out of this principal-agent relationship are very

similar to the ones existent in the user-marketplace relationship. Providers are also

concerned about the neutrality of the marketplace operator, about his technological

ability, his ability to set standards as well as the soundness of the marketplace

functionalities and of the behavior of the marketplace operator.

‘‘Yes, exactly, the neutrality of the marketplace operator is of course

questionable. I do not think the operator can be neutral. […] For example,

just as an insurance broker can’t be neutral, as he also has his favorite

customers and that is just the way it is. […] With open, transparent quality

criteria, which are regularly reviewed, there will be trust.’’ (interview partner

9)

Since all these aspects have already been discussed in the context of the user-

marketplace-operator relationship, they are only mentioned here but not elaborated

in detail. In addition, the interview partners mentioned two more types of

uncertainty: The first one deals with concerns about a loss of responsibilities, e.g.

concerning the product design, the contract design, and the design of the interfaces.

This concern is existent pre- and post-contractually: The interviewees are especially

afraid of changes in the offerings’ design they are not in accord with and cannot

influence. The second uncertainty relates to a potential loss of reputation through the

participation in a malfunctioning marketplace and thus unsatisfied customers.

‘‘I would thoroughly inquire what is behind the marketplace, what kind of

intention MarketMaker has and […] elicit this significantly. It is a piece of our

reputation, which is transferred there. […] Since we have made the conscious

decision to become a serious supplier in the market […] we do not want to

mess anything up, if we go in cooperation with amateurish marketplace

operators.’’ (interview partner 7)

This concern also comprises adverse selection and moral hazard problems since

the provider can never be sure whether complications with the marketplace happen.

Figure 4 provides a comprehensive picture of all uncertainties introduced through

the marketplace operator.

4.4 Cloud-market success factors

In the following, mechanisms which can help to mitigate the uncertainty introduced

by the marketplace operator are presented. Since the mitigators are very similar for

S. Hauff et al.

123

both relationships, they are discussed in combination. A high level of transparency

constitutes the first possibility of uncertainty reduction.

‘‘To get this, it is a crucial success factor […] to make the structure of the

marketplace, our admission criteria, our SLAs and so on, transparent and also

communicate this to our all market participants.’’ (interview partner 12)

For instance, the marketplace operator can openly communicate the structure of

the marketplace, his matching mechanisms, the admission criteria, and the SLAs, to

name but a few examples. Thereby, he can show that he is a neutral instance and

that users and providers can trust in him. Moreover, the marketplace can offer a

transparent feedback mechanism where providers as well as users can see the

feedback about other participants. This enhances the perceived transparency and

neutrality. In addition, external control mechanisms of trusted third parties can

create trust in the marketplace, e.g. certificates issued by an auditing organization

with an excellent reputation.

‘‘I think everything should be a third-party-certified or it should at least be

assured that everything is above board […], in terms that nothing is tricked in

the background, for example that one provider gets more information than

another and so on. […] of course there has to be a certificate on it somehow

[…].’’ (interview partner 10)

Furthermore, the marketplace operator can offer potential participants to include

them in the conceptual as well as in the implementation phase of the marketplace as

MarketMaker currently plans to do. This constitutes a further signal: On the one

hand, all parties can represent and articulate their interests so that they might be

considered in the design. On the other hand, they can also gain detailed insights into

the marketplace design and check the soundness of the functionalities. Thus, it can

increase the trust in the marketplace. An excellent reputation is a fourth signaling

construct which can reduce uncertainty. As discussed above, an organization aims at

keeping its good reputation since it is an important asset for future business.

Fig. 4 Uncertainties between marketplace operator and participants

Exploring uncertainties in a marketplace for cloud computing

123

Moreover, especially for consumers who are currently only hesitantly using cloud

computing and for providers who have no experience with marketplaces, a

marketplace operator with a well-known brand name can establish trust in his

services.

‘‘But I think because it is MarketMaker you know that you can rely on them.

So if you can handle transactions in shares, then maybe you should be able to

do a few transactions on a cloud market.’’ (interview partner 10)

Allowing the participants to test and challenge the marketplace can also increase

confidence in the system because they do not have to believe in another party but

can test the functionalities themselves. This might not only include trying out the

functionalities but also penetration tests to assess the security of the marketplace.

‘‘Therefore, we would be happy if we could conduct security penetration tests

with the interfaces of the marketplace system, because everything is

transferred over these.’’ (interview partner 4)

This last mitigator belongs to the category of monitoring mechanisms. Figure 5

summarizes the mitigators graphically.

5 Discussion

The objective of this study is to develop a theoretical framework for understanding

uncertainties surrounding cloud markets for highly standardized computing

resources and the trade-offs they imply for an adoption decision. Overall, our

results and interpretations show that agency problems are prevalent in cloud markets

and that the principal-agent theory is a well chosen theoretical perspective to

contribute to understanding participants’ behavior. It is particularly suitable as a

theoretical scaffold for our study, since information asymmetries between cloud

provider and user play a major role in the existence of uncertainties preceding the

Fig. 5 Uncertainty mitigators between marketplace operator and participants

S. Hauff et al.

123

adoption of a cloud market by participants. The key findings that provide new

insights on uncertainties surrounding cloud computing marketplaces are discussed

in detail in the following. Subsequently, the theoretical and practical contributions

as well as suggestions for future research are presented.

5.1 Key findings

Our study corroborates previous research on cloud computing that has also

identified information privacy (e.g., Takabi et al. 2010), information security (e.g.,

Miyazaki and Fernandez 2000), availability (e.g., Sandhu et al. 2010), and lock-in

(e.g., Armbrust et al. 2010) concerns as the major sources of uncertainties in cloud

computing service scenarios. Also, the mitigating opportunities of a cloud market

operator are similar to what has been discussed in previous research on success

factors of cloud providers (e.g., Armbrust et al. 2010; Parameswaran and Chaddha

2009).

In contrast, our empirical findings provide new insights on cloud-market-specific

uncertainties that are introduced by the cloud market and insights on how these

uncertainties can be successfully managed by the marketplace operator. Based on

our findings, we are able to better assess whether a cloud market is a more attractive

alternative for cloud providers and users as opposed to a direct and bilateral cloud

provider-user business relationship. Our key findings have important implications

for the feasibility of a cloud market in a business-to-business context and the

question how organizations will obtain highly standardized IT resources in the

future.

5.1.1 The cloud market from a user perspective

Users currently face a variety of uncertainties in bilateral relationships with cloud

providers which have also been examined in previous research (Armbrust et al.

2010; Venters and Whitley 2012). Using the principal-agent perspective, we

describe in Sect. 4.1 that uncertainties exist between users and providers: Users are

especially concerned about data privacy and security, but also fear non-availability

and a provider lock-in. A marketplace operator who steps into this relationship can

help to mitigate these uncertainties through mechanisms like admission criteria and

monitoring as presented in Sect. 4.2. The acquisition of cloud resources gets easier

and more attractive for users and thus can be an improvement of the current

situation. Overall, our analysis reveals that a marketplace has a better ability to

mitigate uncertainties compared to cloud providers as the marketplace serves as a

neutral and competent instance between cloud provider and user.

Besides these positive effects, our findings also show that such an intermediary

introduces additional uncertainties from a user perspective, e.g. regarding the

functionality and availability of the marketplace or its neutrality, as discussed in

Sect. 4.3. Therefore, obtaining cloud resources becomes again more risky for users

on the marketplace. On the other hand, the market operator has abilities to reduce

these uncertainties. Our study reveals that users are more likely to adopt and use a

cloud market which operates under a trustworthy brand, they rely on well-

Exploring uncertainties in a marketplace for cloud computing

123

established external control mechanisms and favor an early integration of users in

the design and building phase of the marketplace, to name some mitigators

presented in Sect. 4.4. Overall, our study indicates that a cloud market can be an

attractive alternative for cloud users compared to a bilateral and direct business

relationship with cloud providers.

5.1.2 The cloud market from a cloud provider perspective

For cloud providers, the situation is quite different compared to the user perspective

discussed in the previous section. In a bilateral relationship with cloud users, a

provider faces only minor uncertainties like the user’s financial solvency. Thus,

being the agent in this relationship is fruitful for the provider and rather risk-free.

The introduction of an intermediary into this picture arouses many potential

uncertainties for a provider: as our analysis in Sect. 4.3 shows, providers are

especially concerned about the functionality of the marketplace as well as the

neutrality of its operator. Moreover, they fear a potential loss of responsibility and

reputation since they no longer have full control over the way and the reliability in

which their services are delivered. The uncertainty mitigators we present in Sect. 4.4

are also relevant to the cloud providers. For them, the transparency of the

marketplace mechanisms and a strong reputation are of major interest.

Overall, the cloud market causes several types of uncertainties for the provider

but offers only risk reduction for cloud users. However, some compensation or

benefit could be gained by using a cloud market. Cloud providers can use it as an

additional sales channel for customers that only rely on the CloudMarket but not on

the cloud providers’ reputation. Also, small data centers which only have limited

capacity can fulfill large orders because they have to provide only a part of the

service, the rest can be served by another provider in a way that is transparent to the

user. Thus, in the end, the provider has to decide whether these benefits really

compensate for all additionally introduced uncertainties and whether he wants to

participate in the marketplace. Therefore, seeing it from an uncertainty perspective,

the marketplace presents a less attractive alternative to the current bilateral

relationships.

5.2 Theoretical contribution and implications for research

Our paper presents the first empirical study on a conceptualized multi-vendor,

multi-buyer, third party operated marketplace for cloud computing. Some concep-

tual studies have been carried out on the technical feasibility of such markets (e.g.,

Buyya et al. 2008; Schnizler et al. 2008). However, the conceptual evaluation of

such market mechanisms showed that the clearing of the market is far too complex

to carry it out in practice in the way the authors propose. Also, major issues of data

privacy, risk mitigation and service level enforcement remain open. Our study

shows that the motives for adopting a transparent, two-sided and independently

managed marketplace for cloud computing are distinct to those identified in

previous research on e-market adoption and that uncertainties between cloud

provider, user and market operator play a major role for the feasibility of such a

S. Hauff et al.

123

market place. Even more, while the marketplace is an attractive alternative to the

bilateral relationships for users, providers also experience new uncertainties in these

constellations. Nonetheless, if satisfying compensation can be offered to providers,

a cloud marketplace might be a promising way of trading cloud computing

resources in the future. Yet, this trilateral contract as efficient governance structure

might contradict some elements of the transaction cost theory: The theory says that

trilateral contracts are only the most suitable solution in case of occasional

transactions and mixed or idiosyncratic asset specificity (Williamson 1975). The

marketplace, however, is also used for frequent transactions and the related asset

specificity is non-specific or mixed due to the intended high degree of standard-

ization on the marketplace. Thus, this tentative finding should be subject of further

investigations in the near future.

Overall, we provide three major-contributions to the literature on cloud

computing. First, our study shows that agency problems are prevalent on cloud

markets and that the principal-agent theory is a fruitful perspective to study these

uncertainties. Since the perspective has hardly been used to study the adoption of

e-markets, we encourage future research to re-examine other theoretical e-market

contexts based on this perspective. Second, while cloud markets have capabilities to

mitigate uncertainties between cloud provider and user, they also cause new

uncertainties in this relationship. This supplements previous studies which have

emphasized and theorized the mitigating capabilities of e-markets but did not focus

on their negative effects on uncertainty perceptions of participants. Third and as

presented in the previous section, our study presents a second-level theoretical

understanding on uncertainties surrounding cloud markets and thereby sheds light

on the trade-offs involved in the decision to adopt a cloud market by cloud providers

and users. The framework can be utilized by future research to study the role of

uncertainty for other relevant behavioral outcomes in the context of cloud

computing and cloud markets in particular.

5.3 Implications for practice

Several implications for practitioners can be given. First, the framework can help

market operators in the design of the marketplace. Since uncertainty demonstrably

plays a dominant role, we want to raise market operators’ awareness for this topic:

They can reduce the uncertainties inherent in the bilateral relationships between

users and providers like offering warranties and monitoring. Thus, it is advanta-

geous to clearly communicate all mitigating capabilities a marketplace offers.

Moreover, the marketplace’s potential of uncertainty reduction is also an interesting

aspect for cloud providers since they are not only competing for current cloud users

but also for new user segments which are currently not using cloud services due to

the existing risks.

On the other hand, market operators have to keep in mind that they and their

marketplaces are also a source of uncertainty. Therefore, they should concentrate on

mitigating the concerns, e.g. by building up trust and openly and transparently

communicating all functionalities of a marketplace. Moreover, an early integration

of potential participants in the conceptual phase can increase the probability of

Exploring uncertainties in a marketplace for cloud computing

123

acceptance. While the overall degree of uncertainty is reduced for users, market

operators should carefully consider the compensations they offer to providers since

they face a higher degree of uncertainty when participating in the marketplace

compared to trading in bilateral relationships.

The third implication deals with the differences of cloud users and cloud

providers. Market operators should address both groups separately as they have

different concerns when participating in the marketplace. Therefore, market

operators should carefully think about how to present the idea of their marketplace

to each of these groups in order to get the best out of each meeting or advertising

campaign, for instance.

References

AIS (2011) Association of information systems, Georgia. http://start.aisnet.org/?SeniorScholarBasket.

Accessed 30 Jan 2013

Akerlof GA (1970) The market for ‘lemons’: quality uncertainty and the market mechanism. Q J Econ

84:488–500. doi:10.2307/1879431

Alford T, Morton G (2009) The economics of the cloud—addressing the benefits of infrastructure in the

cloud. http://www.boozallen.com/media/file/Economics-of-Cloud-Computing.pdf. Accessed 27 Nov

2013

Angeles R (2000) Revisiting the role of internet-EDI in the current electronic commerce scene. Logist Inf

Manag 13:45–57. doi:10.1108/0957605001030639

Appelbaum PS, Gold A (2010) Psychiatrists’ relationships with industry: the principal-agent problem.

Harv Rev Psychiatry 18:255–265. doi:10.3109/10673229.2010.507038

Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, Lee G, Patterson D, Rabkin A, Stoica

I, Zaharia M (2010) A view of cloud computing. Commun Assoc Comput Mach 53:50–58. doi:10.

1145/1721654.1721672

Bakos JY (1991) A strategic analysis of electronic marketplaces. Manag Inf Syst Q 15:295–310. doi:10.

2307/249641

Bakos JY (1997) Reducing buyer search costs: implications for electronic marketplaces. Manag Sci

43:1676–1692. doi:10.1287/mnsc.43.12.1676

Bakos JY (1998) The emerging role of electronic marketplaces on the internet. Commun Assoc Comput

Mach 41:35–42. doi:10.1145/280324.280330

BITKOM (2012) Bundesverband Informationswirtschaft, Telekommunikation und neue Medien e.V.,

Berlin. http://www.bitkom.org/de/markt_statistik/64086_71376.aspx. Accessed 30 Jan 2013

Breskovic I, Altmann J, Brandic I (2012) Creating standardized products for electronic markets. Future

Gener Comput Syst 29:1000–1011. doi:10.1016/j.future.2012.06.007

Buyya R, Yeo CS, Venugopal S (2008) Market-oriented cloud computing: vision, hype, and reality for

delivering IT services as computing utilities. Paper presented at the 10th IEEE international

conference on high performance computing and communications, Dalian, China, 25–27 Sept 2008

Buyya R, Pandey S, Vecchiola C (2009a) Cloudbus toolkit for market-oriented cloud computing. In:

Jaatun MG, Zhao G, Rong C (eds) Cloud computing. Springer, Berlin, Heidelberg, pp 24–44

Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I (2009b) Cloud computing and emerging IT

platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener Comput

Syst 25(6):599–616. doi:10.1016/j.future.2008.12.001

Calheiros RN, Toosi AN, Vecchiola C, Buyya R (2012) A coordinator for scaling elastic applications

across multiple clouds. Future Gener Comput Syst 28:1350–1362. doi:10.1016/j.future.2012.03.010

Carr NG (2003) IT doesn’t matter. Harv Bus Rev 81:1–32. doi:10.1109/EMR.2004.25006

Chang HH, Wong KH (2010) Adoption of e-procurement and participation of e-marketplace on firm

performance: trust as a moderator. Inf Manag 47:262–270. doi:10.1016/j.im.2010.05.002

Coase RH (1937) The Nature of the Firm. Economica 4:386–405. doi:10.1111/j.1468-0335.1937.tb00002.x

S. Hauff et al.

123

Datta P, Chatterjee S (2008) The economics and psychology of consumer trust in intermediaries in

electronic markets: the EM trust framework. Eur J Inf Syst 17:12–28. doi:10.1057/palgrave.ejis.

3000729

Delgado-Ballester E, Munuera-Aleman JL (2001) Brand trust in the context of consumer loyalty. Eur J

Mark 35:1238–1258. doi:10.1108/EUM0000000006475

Dimoka A, Hong Y, Pavlou P (2012) On product uncertainty in online markets: theory and evidence.

Manag Inf Syst Q 36:395–426

Eisenhardt KM (1989a) Agency theory: an assessment and review. Acad Manag Rev 14:57–72. doi:10.

2307/258191

Eisenhardt KM (1989b) Building theories from case study research. Acad Manag Rev 14:532–550.

doi:10.5465/AMR.1989.4308385

Foster I, Zhao Y, Raicu I, Lu S (2008) Cloud computing and grid computing 360-degree compared. Paper

presented at grid computing environments workshop, 2008. GCE’08, Austin, US, 12–16 Nov 2008

Garg SK, Vecchiola C, Buyya R (2011) Mandi: a market exchange for trading utility and cloud

computing services. J Supercomput 64:1153–1174. doi:10.1007/s11227-011-0568-6

Gartner (2012) Gartner says worldwide cloud services market to surpass $109 billion in 2012. http://

www.gartner.com/newsroom/id/2163616. Accessed 30 Jan 2013

Gengatharen DE, Standing C (2005) A framework to assess the factors affecting success or failure of the

implementation of government-supported regional e-marketplaces for SMEs. Eur J Inf Syst

14:417–433. doi:10.1057/palgrave.ejis.3000551

Giaglis GM, Klein S, O’Keefe RM (2002) The role of intermediaries in electronic marketplaces:

developing a contingency model. Inf Syst J 12:231–246. doi:10.1046/j.1365-2575.2002.00123.x

Gordon RL (1980) Interviewing, strategy, techniques and tactics. Dorsey Press, Homewood, IL

Grance T, Mell PM (2011) The NIST definition of cloud computing. US Department of Commerce. http://

www.nist.gov/manuscript-publication-search.cfm?pub_id=909616. Accessed 29 Feb 2012

Grilo A, Jardim-Goncalves R (2013) Cloud-marketplaces: distributed e-procurement for the AEC sector.

Adv Eng Inf 27:160–172. doi:10.1016/j.aei.2012.10.004

Hoffer A (1985) Toward a definition of psychoanalytic neutrality. J Am Psychoanal Assoc 33:771–795.

doi:10.1177/000306518503300402

Holton JA (2007) The coding process and its challenge. In: Charmaz K, Bryant A (eds) The sage

handbook of grounded theory. Sage Publications, London, pp 265–290

Jensen MC, Meckling WH (1976) Theory of the firm: managerial behavior, agency costs and ownership

structure. J Financ Econ 3:305–360. doi:10.1016/0304-405x(76)90026-x

Joo YB, Kim YG (2004) Determinants of corporate adoption of e-marketplace: an innovation theory

perspective. J Purch Supply Manag 10:89–101. doi:10.1016/j.pursup.2004.01.001

Kaufman LM (2009) Data security in the world of cloud computing. IEEE Secur Priv 7:61–64. doi:10.

1109/MSP.2009.87

Krieger O, McGachey P, Kanevsky A (2010) Enabling a marketplace of clouds: VMware’s vCloud

Director. SIGOPS Oper Syst Rev 44:103–114. doi:10.1145/1899928.1899942

Lee A (1991) Integrating positivist and interpretive approaches to organizational research. Organ Sci

2:342–365. doi:10.1287/orsc.2.4.342

Lenk A, Klems M, Nimis J, Tai S, Sandholm T (2009) What’s inside the cloud? An architectural map of

the cloud landscape. Paper presented at proceedings of the 2009 ICSE workshop on software

engineering challenges of cloud computing, Washington, USA, 23 May 2009

Li H, Jeng JJ (2010) CCMarketplace: a marketplace model for a hybrid cloud. Paper presented at

proceedings of the 2010 conference of the center for advanced studies on collaborative research,

Toronto, Canada, 1–4 Nov 2010

Malkiel BG, Fama EF (1970) Efficient capital markets: a review of theory and empirical work. J Financ

25:383–417. doi:10.1111/j.1540-6261.1970.tb00518.x

Malone TW, Yates J, Benjamin RI (1987) Electronic markets and electronic hierarchies. Commun Assoc

Comput Mach 30:484–497. doi:10.1145/214762.214766

Mishra DP, Heide JB, Cort SG (1998) Information asymmetry and levels of agency relationships. J Mark

Res 35:277–295. doi:10.2307/3152028

Miyazaki AD, Fernandez A (2000) Internet privacy and security: an examination of online retailer

disclosures. J Public Policy Mark 19:54–61. doi:10.1509/jppm.19.1.54.16942

Mugge D (2011) The European presence in global financial governance: a principal-agent perspective.

J Eur Public Policy 18:383–402. doi:10.1080/13501763.2011.551075

Nelson P (1970) Information and consumer behavior. J Polit Econ 78:2311–2329

Exploring uncertainties in a marketplace for cloud computing

123

Parameswaran AV, Chaddha A (2009) Cloud interoperability and standardization. SETLabs Brief

7:19–26

Patton MQ (2002) Qualitative research and evaluation methods, 3rd edn. Sage, Thousand Oaks

Pavlou PA, Liang H, Xue Y (2007) Understanding and mitigating uncertainty in online exchange

relationships: a principal-agent perspective. Manag Inf Syst Q 31:105–136

Quaddus M, Hofmeyer G (2007) An Investigation into the factors influencing the adoption of B2B trading

exchanges in small businesses. Eur J Inf Syst 16:202–215. doi:10.1057/palgrave.ejis.3000671

Rao A, Ruekert RW (1994) Brand alliances as signals of product quality. Sloan Manag Rev 36:87–97

Rask M, Kragh H (2004) Motives for e-marketplace participation: differences and similarities between

buyers and suppliers. Electron Mark 14:270–283. doi:10.1080/10196780412331311720

Rossbach C, Welz B (2011) Survival of the fittest—how europe can assume a leading role in the cloud.

Roland Berger strategy consultans. http://www.rolandberger.com/media/pdf/Roland_Berger_

Cloud_Ecosystem_D_20111130.pdf. Accessed 19 June 2012

Sandhu R, Boppana R, Krishnan R, Reich J, Wolff T, Zachry J (2010) Towards a discipline of mission-

aware cloud computing. In Proceedings of the 2010 ACM workshop on cloud computing security

workshop, New York, US. doi:10.1145/1866835.1866839

Sarker S, Sarker S (2009) Exploring agility in distributed information systems development teams: an

interpretive study in an offshoring context. Inf Syst Res 20:440–461. doi:10.1287/isre1090.0241

Sarker S, Sahaym A, Bjorn-Andersen N (2012) Exploring value cocreation in relationships between an

ERP Vendor and its partners: a revelatory case study. Manag Inf Syst Q 36:317–338

Schepers J, Falk T, de Ruyter K, de Jong AD, Hammerschmidt M (2012) Principles and principals: do

customer stewardship and agency control compete or complement when shaping frontline employee

behavior? J Mark 76:1–20. doi:10.1509/jm.11.0112

Schnizler B, Neumann D, Veit D, Weinhardt C (2008) Trading grid services—a multi-attribute

combinatorial approach. Eur J Oper Res 187:943–961

Smith A (1937[1776]) The Wealth of Nations. In: Cannan E (ed) Reprint, 1904. Modern Library, New

York

Son JY, Tu L, Benbasat I (2006) A descriptive content analysis of trust-building measures in B2B

electronic marketplaces. Commun Assoc Inf Syst 18:99–128

Stockdale R, Standing C (2004) Benefits and barriers of electronic marketplace participation: an SME

perspective. J Enterp Inf Manag 17:301–311. doi:10.1108/17410390410548715

Strausz R (1997) Delegation of monitoring in a principal-agent relationship. Rev Econ Stud 64:337–357.

doi:10.2307/2971717

Takabi H, Joshi JBD, Ahn GJ (2010) Security and privacy challenges in cloud computing environments.

IEEE Secur Priv 8:24–31. doi:10.1109/MSP.2010.186

Tao YH, Chen CP, Chang CR (2007) Unmet adoption expectation as the key to e-marketplace failure: a

case of Taiwan’s steel industry. Ind Mark Manag 36:1057–1067. doi:10.1016/j.indmarman.2006.08.

004

Venters W, Whitley EA (2012) A critical review of cloud computing: researching desires and realities.

J Inf Technol 27:179–197. doi:10.1057/jit.2012.17

Vermillion LJ, Lassar WM, Winsor RD (2002) The Hunt-Vitell general theory of marketing ethics: can it

enhance our understanding of principal-agent relationships in channels of distribution? J Bus Ethics

41:267–285. doi:10.1023/A:1021284922440

Walsham G (1995) Interpretive case studies in IS research: nature and method. Eur J Inf Syst 4:74–81.

doi:10.1057/ejis

Westin AF (1967) Privacy and freedom. Atheneum Press, New York

Wigand RT (1997) Electronic commerce: definition, theory, and context. Inf Soc 13:1–16. doi:10.1080/

019722497129241

Williamson OE (1975) Markets and hierarchies. The Free Press, New York

Williamson OE (1985) The economic institutions of capitalism: firms, markets, relational contracting.

The Free Press, New York

Yin RK (2009) Case study research: design and methods, 4th edn. SAGE Publications, Thousand Oaks

Zhang Q, Cheng L, Boutaba R (2010) Cloud computing: state-of-the-art and research challenges.

J Internet Serv Appl 1:7–18. doi:10.1007/s13174-010-0007-6

S. Hauff et al.

123